Abstract: Disclosed are various embodiments directed toward applying a magnetic resistance to a human powered vehicle during movement. In various embodiments, magnets are placed within receptacles of magnet holding brackets and are exposed to one or more conducting discs that are configured to spin with the wheels of the human powered vehicle. The magnetic field of the magnets that intersect the conducting discs can generate a force that opposes the movement of the human powered vehicle. In various embodiments, the magnet holding brackets are adjustable based on desired wattage values.

Abstract: Disclosed are various embodiments for high diffraction efficiency phase gratings. An organized set of nanoparticles are embedded within a polymer composite. The polymer composite is then etched to generate one or more trenches in the polymer composite that correspond to the organized set of nanoparticles.

Abstract: An auto-adaptive system is provided that includes a template builder that allows weighted templates to be created for computing auto-adaptive features, an auto-adaptive event locator that analyzes a data set to identify events, an event extractor that locates and extracts identified events and provides events for review by an event analyzer (operator or programmed module) to distinguish clutter data from target data, and an auto-adaptive risk analyzer that processes data related to hit rates, false alarm rates, alarm costs, and risk factors to determine return on investment information and receiver operator characteristic curves.

Abstract: Feature values, which may be multi-dimensional, collected over successive time slices, are efficiently processed for use, for example, in known adaptive learning functions and event detection. A Markov chain in a recursive function to calculate imputed values for data points by use of a “nearest neighbor” matrix. Only data for the time slices currently required to perform computations must be stored. Earlier data need not be retained. A data selector, referred to herein for convenience as a window driver, selects successive cells of appropriate adjacent values in one or more dimensions to comprise an estimation set. The window driver effectively indexes tables of data to efficiently deliver input data to the matrix. In one form, feature inputs are divided into subgroups for parallel, pipelined processing.

Abstract: An auto-adaptive system is provided that includes a template builder that allows weighted templates to be created for computing auto-adaptive features, an auto-adaptive event locator that analyzes a data set to identify events, an event extractor that locates and extracts identified events and provides events for review by an event analyzer (operator or programmed module) to distinguish clutter data from target data, and an auto-adaptive risk analyzer that processes data related to hit rates, false alarm rates, alarm costs, and risk factors to determine return on investment information and receiver operator characteristic curves.